29 citations as recorded by crossref.

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4. Machine Learning-Based Target Classification for MMW Radar in Autonomous Driving X. Cai et al. https://doi.org/10.1109/TIV.2020.3048944
5. Automatic Radar-Camera Dataset Generation for Sensor-Fusion Applications A. Sengupta et al. https://doi.org/10.1109/LRA.2022.3144524
6. Microwave Microphone Using a General Purpose 24-GHz FMCW Radar E. Guerrero et al. https://doi.org/10.1109/LSENS.2020.2997978
7. Review of Vehicle Detection Systems in Advanced Driver Assistant Systems K. Sakhare et al. https://doi.org/10.1007/s11831-019-09321-3
8. Pedestrian Detection in Blind Area and Motion Classification Based on Rush-Out Risk Using Micro-Doppler Radar S. Hayashi et al. https://doi.org/10.3390/s21103388
9. Multiple Attention Mechanism for Camera-Radar Fusion Object Detection W. Wang et al. https://doi.org/10.1109/TVT.2025.3531379
10. 300 GHz radar object recognition based on deep neural networks and transfer learning M. Sheeny et al. https://doi.org/10.1049/iet-rsn.2019.0601
11. Range-Max Enhanced Ultrawideband Micro-Doppler Signatures of Behind-the-Wall Indoor Human Motions Q. An et al. https://doi.org/10.1109/TGRS.2021.3122138
12. Pedestrian Detection by Template Matching Using Gabor Filter Bank on 24GHz UWB Radar K. IWANAGA et al. https://doi.org/10.1587/transfun.E100.A.232
13. A Novel Approach for Model-Based Pedestrian Tracking Using Automotive Radar P. Held et al. https://doi.org/10.1109/TITS.2021.3066680
14. Point Cloud Features-Based Kernel SVM for Human-Vehicle Classification in Millimeter Wave Radar Z. Zhao et al. https://doi.org/10.1109/ACCESS.2020.2970533
15. Height-Finding for Automotive THz Radars S. Shishanov et al. https://doi.org/10.1109/TITS.2018.2845542
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17. On the Detection of Vulnerable Road Users—Simulating Limits of an FMCW Radar F. Yüksekkaya et al. https://doi.org/10.3390/electronics13132547
18. Multiposture leg tracking for temporarily vision restricted environments based on fusion of laser and radar sensor data N. Mandischer et al. https://doi.org/10.1002/rob.22195
19. Automated Vehicles and Pedestrian Safety: Exploring the Promise and Limits of Pedestrian Detection T. Combs et al. https://doi.org/10.1016/j.amepre.2018.06.024
20. Application of Deep Learning on Millimeter-Wave Radar Signals: A Review F. Abdu et al. https://doi.org/10.3390/s21061951
21. RADIO: Parameterized Generative Radar Data Augmentation for Small Datasets M. Sheeny et al. https://doi.org/10.3390/app10113861
22. A Survey of Pedestrian Re-Identification Based on Millimeter Wave Radar and Vision Fusion Q. Yang et al. https://doi.org/10.4236/jcc.2025.136005
23. Detecting Darting Out Pedestrians With Occlusion Aware Sensor Fusion of Radar and Stereo Camera A. Palffy et al. https://doi.org/10.1109/TIV.2022.3220435
24. The Application of Machine Learning and Deep Learning with a Multi-Criteria Decision Analysis for Pedestrian Modeling: A Systematic Literature Review (1999–2023) P. Reyes-Norambuena et al. https://doi.org/10.3390/su17010041
25. Radar Signal Processing for Jointly Estimating Tracks and Micro-Doppler Signatures T. Wagner et al. https://doi.org/10.1109/ACCESS.2017.2667720
26. Automotive Radar Processing With Spiking Neural Networks: Concepts and Challenges B. Vogginger et al. https://doi.org/10.3389/fnins.2022.851774
27. Millimeter-Wave Radar and Vision Fusion Target Detection Algorithm Based on an Extended Network C. Qi et al. https://doi.org/10.3390/machines10080675
28. High Fidelity Physics Simulation-Based Convolutional Neural Network for Automotive Radar Target Classification Using Micro-Doppler U. Chipengo et al. https://doi.org/10.1109/ACCESS.2021.3085985
29. Autonomous Driving: A Survey of Technological Gaps Using Google Scholar and Web of Science Trend Analysis S. Hacohen et al. https://doi.org/10.1109/TITS.2022.3172442